Sr Analysts, Credit Risk Mgmt

T-Mobile•Bellevue, WA

1d•$146,182 - $153,800•Hybrid

About The Position

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees! T-Mobile is America’s supercharged Un-carrier, delivering an advanced 4G LTE and transformative nationwide 5G network that will offer reliable connectivity for all. Sr Analysts, Credit Risk Management is located in Bellevue, WA will analyze customer behavior to inform and refine credit strategies. • Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week. No additional national or international travel is anticipated. Position duties and responsibilities include, but are not limited to: Forecast financial trends to support strategic decision-making. Evaluate and optimize the effectiveness of credit policies and outcomes. Develop customer risk segments to improve credit management and performance. Utilize statistical segmentation techniques to identify new opportunities. Performing complex qualitative and quantitative analysis of credit polices to ensure financial goals are being attained. Developing predictive financial and analytical models using the appropriate statistical methodologies, including trend and regression analysis. Participate and perform the analysis of new data and statistical products by external vendors. Performing loss forecasting analysis. Extracting, processing and transforming data from multiple disparate sources. Analyzing credit bureau data and alternative credit data.

Requirements

Bachelor’s degree in Computer Science, Computer Programming, Computer Engineering, Business Administration, or related, and 5 years of relevant work experience in any occupation in which the required experience is gained.
Master’s degree in Computer Science, Computer Programming, Computer Engineering, Business Administration, or related, and 3 years of experience in any occupation in which the required experience is gained.
SQL, Excel VBA or analytical programming language R to manipulate and analyze large-scale datasets, derive critical insights, and translate complex findings into clear, actionable recommendations tailored for Executive Leadership
Snowflake, CV, CUW, or Teradata to extract, transform, and integrate data from multiple sources, with knowledge in managing the full Exploratory Data Analysis (EDA) lifecycle, including advanced querying, feature engineering, and building/managing data tables to ensure accuracy
Lead data-driven initiatives from requirements gathering to analytical framework design, with proficiency in leveraging statistical methods in R or Python including decision trees, regression models, and K-means clustering to enhance customer segmentation and credit risk strategies
Develop executive-level visualizations and performance tracking dashboards using Tableau, Power BI, SQL, Excel/VBA, and Python including pandas, matplotlib, and seaborn by performing ETL/data engineering including Extraction, Transformation, and Loading to deliver insights and monitor key metrics
Develop financial models and forecasts: Customer Lifetime Value prediction, cohort analysis, scenario modeling, using Excel, SQL, Python including NumPy, pandas, and scikit-learn to evaluate strategies and drive growth
Manage credit risk and underwriting by applying knowledge of credit structures and leveraging transactional, payment, and consumer behavioral data to build predictive models and develop optimization models in Excel and Python to design and implement new credit initiatives
At least 18 years of age
Legally authorized to work in the United States

Responsibilities

Forecast financial trends to support strategic decision-making.
Evaluate and optimize the effectiveness of credit policies and outcomes.
Develop customer risk segments to improve credit management and performance.
Utilize statistical segmentation techniques to identify new opportunities.
Performing complex qualitative and quantitative analysis of credit polices to ensure financial goals are being attained.
Developing predictive financial and analytical models using the appropriate statistical methodologies, including trend and regression analysis.
Participate and perform the analysis of new data and statistical products by external vendors.
Performing loss forecasting analysis.
Extracting, processing and transforming data from multiple disparate sources.
Analyzing credit bureau data and alternative credit data.